Analytical considerations in the use of capture-recapture to estimate prevalence: case studies of the estimation of opiate use in the metropolitan area of Barcelona, Spain

Am J Epidemiol. 1998 Oct 15;148(8):732-40. doi: 10.1093/oxfordjournals.aje.a009694.

Abstract

Capture-recapture, an indirect method widely used to estimate undetected populations, has been criticized because it causes problems due to a lack of compliance with several important assumptions and model selection strategies. This paper expands on the problems encountered when applying this methodology to drug abuse estimations, specifically the prevalence of opiate use in the metropolitan area of Barcelona, Spain, in 1993. Three samples of opiate users (from hospital emergency rooms, treatment centers, and prisons) were available in the area studied; an additional sample (mortality data) was analyzed for the city of Barcelona. Log-linear models that provided a good fit were considered, to which further model selection strategies were applied. A total of 3,207 unique individuals aged 15-44 years were identified in the three samples from the greater Barcelona area; the mortality sample from the city of Barcelona contained an additional 83 individuals. Heterogeneity was observed in different age, sex, and residence area subgroups. Population estimates differed widely according to the log-linear model chosen. Minimum Akaike's information criterion model and saturated model estimates were used to produce population prevalence rates. The main problems the authors encountered in this study were related to population definition, source heterogeneity, and assessment of an adequate model, a problem associated with sample size.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Distribution
  • Case-Control Studies
  • Epidemiologic Methods*
  • Female
  • Humans
  • Linear Models
  • Logistic Models
  • Male
  • Opioid-Related Disorders / epidemiology*
  • Prevalence
  • Sex Distribution
  • Spain / epidemiology
  • Urban Health / statistics & numerical data